Love Your Data Week Feb 13th – 17th 2017

February 14th: Documenting, Describing, Defining

Post authored by Lora Leligdon

For the second day of Love Your Data week, we will be discussing good data documentation!

Good documentation tells people they can trust your data by enabling validation, replication, and reuse.

Things to consider:

Why does having good documentation matter?

It contributes to the quality and usefulness of your research and the data itself – for yourself, colleagues, students, and others.

It makes the analysis and write-up stages of your project easier and less stressful.

It helps your teammates, colleagues, and students understand and build on your work.

It helps to build trust in your research by allowing others to validate your data or methods.

It can help you answer questions about your work during pre-publication peer review and after publication.

It can make it easier for others to replicate or reuse your data. When they cite the data, you get credit! Include these citations in your CV, funding proposal, or promotion and tenure package.

It improves the integrity of the scholarly record by providing a more complete picture of how your research was conducted. This promotes public trust and support of research!

Some communities and fields have been talking about documentation for decades and have well-developed standards for documentation (e.g., geospatial data, clinical data, etc.), while others do not (e.g., psychology, education, engineering, etc.). No matter where your research community or field falls in this spectrum, you can start improving your documentation today!

README files are a simple and low-tech way to start documenting your data better. Check out the sample readme.txt (filename = readme_template.txt) from IU or Cornell University’s data working group guide with tips for using readme files